Love In Faith Company logo on Dataaxy
Love In Faith

Data Engineer

📍
Anaheim, California, United States
🧪
Mid-Level
🏠
Remote friendly

This is a fully remote position within the United States.

About Love in Faith

Love in Faith is an energetic, fast-growing e-commerce company that focuses on Christian apparel. We pride ourselves on delivering top-quality products and a unique shopping experience for our customers.

Here's why you should consider us:

  1. Rapid Growth: We're not your typical startup. Our exponential growth speaks volumes about the opportunities that await you. Be part of something big!
  2. Remote Flexibility: Enjoy the freedom to work from your preferred location, without sacrificing your career goals.
  3. Culture: Our team knows how to work hard and play harder. We value creativity, innovation, and a positive work environment. Join us in celebrating successes, big and small.

About the Role

We are seeking a highly skilled and experienced Data Engineer to join our team. The successful candidate will be responsible for building, maintaining, and optimizing our ETL pipelines. You will play a key role in ensuring our data architecture supports our rapid growth and enables us to extract meaningful insights from complex data sets.

Responsibilities:

  • Design, build, and maintain scalable and reliable ETL pipelines to support data integration from various sources.
  • Develop and manage databases using BigQuery, MySQL & Pinecone, ensuring data integrity, security, and performance.
  • Collaborate with cross-functional teams, to gather requirements and deliver data solutions that support business initiatives.
  • Implement data warehousing solutions and data modeling practices to support advanced analytical and reporting capabilities.
  • Optimize data flow and collection to improve data accuracy and value.
  • Ensure compliance with data governance and data security requirements.
  • Monitor and troubleshoot performance issues on the data pipelines and databases.
  • Stay up-to-date with industry standards and advancements in data engineering practices and technologies
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • Minimum of 3 years of experience in a Data Engineering role.
  • Proficient in SQL and experience with database management systems, particularly BigQuery and MySQL.
  • Demonstrable experience with Shopify’s REST & GraphQL APIs.
  • Experience with data pipeline and workflow management tools.
  • Strong understanding of ETL techniques and best practices.
  • Proficient in one or more programming languages (Python preferred)
  • Experience with cloud services (e.g., AWS, Google Cloud Platform) and understanding of cloud-based ETL services.
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and collaboration abilities to work with team members and stakeholders.

Nice to Have:

  • Experience with data visualization tools and dashboard development.
  • Experience with vector databases
  • Knowledge of machine learning and statistical modeling is a plus.

Physical Demands:

While performing the duties of this job, the employee routinely is required to sit; walk; talk and hear; use hands to keyboard, finger, handle, and feel; stoop, kneel, crouch, twist, reach, and stretch. Speaking and hearing ability sufficient to communicate in person, over the telephone, and/or via video conference.

  • The ability to stand, walk, and sit in a computer chair for long periods of time.
  • The ability to see and respond to dangerous situations.
  • Speaking and hearing ability sufficient to communicate in person, over the telephone and/or via video conferences.
  • Sufficient hand, arm, and finger dexterity to operate a computer keyboard and other office equipment.

Emotional Demands:

  • Data analysis & interpretation. You will have to process and review a lot of information from a variety of sources, understand how data is collected, assess data quality, and how to use the information.
  • Communication skills. You need to have advanced communication skills in both oral and written form. Emails and written communication with colleagues and external partners, written reports for senior executives. Able to communicate complex financial information to people outside of the finance department.
  • Comfortable with technology. Able to navigate data through computers, mobile, software, databases. Stay up to date with technology advances.
  • Oriented to detail. Financial forecasts rely on projections which can be impacted by even minor changes in sales patterns, consumer sentiment, economic shifts, competitor changes, etc. You will need to be attuned to small changes in all streams of data.
  • Confident decision-making skills. You will need to review data and make sound decisions on what actions to take and make confident recommendations to senior management. You may need to make decisions quickly with limited amounts of information in urgent situations.

For Applicants with Disabilities:

Reasonable accommodation will be made for those that qualified during application process. If you need accommodations during the hiring process, please let us know when you submit your application, and we’ll do our very best to adjust as need

  • Medical, Dental, Vision
  • Health Savings (HSA) & Flexible Spending Account (FSA)
  • Company Paid Life Insurance
  • Supplemental Benefits Available
  • Accident Insurance
  • Critical Illness Insurance
  • Unlimited PTO Policy
  • Paid Parental Leave

Other Company Perks:

  • Monthly Utility Stipend
  • Team Meetings Coffee/Food Stipend
  • Health & Wellness Stipend
  • Education & Professional Development Stipend
  • Charitable Gift Matching

Key informations

🧳
Full-time
📅
Posted 15 days ago

Data Engineering
ETL
BigQuery
MySQL
APIs
SQL
Python
Cloud services

Don’t miss out on new
Data & AI Jobs

Get curated job alerts weekly.
Create talent profile

Other jobs at Love In Faith

Love In Faith does not currently have any open job positions in Data & Ai.
© 2023 | All Rights Reserved | Built with 🤍 in MontrealAll our data is gathered from publicly available sources or contributed by users